AI SPECIAL
DOESN'T AI NEED A LOT OF DATA? Artificial intelligence and big data often go hand-in-hand, but generating the kind of enormous datasets required to train an algorithm can come at a big financial and environmental cost. This is why Cambridge’s Prowler.io is doing things differently, working with what CEO Vishal Chatrath describes as “small data” to create its novel AI decision-making platform. “Machine learning relies on lots and lots of data points and lots of information, and for that you need a lot of sensors,” he says. “We don’t believe in this approach, it’s costly and involves putting a lot of plastic and silicon in the world, which isn’t that great from an environmental impact perspective. “Everyone talks about a future where we will need big data, but this is often driven by IT companies trying to sell server space, rather than what can add value for businesses.” While most AI companies base their systems on deep neural networks, algorithms that learn as they are fed more and more data, Prowler’s system uses Gaussian theory, a type of probabilistic modelling that requires a lot less information. Prowler's trick has been to apply this theory at scale, something previously thought to be impractical, so that its AI can help the company’s clients, working in industries such as financial services and logistics, make smarter decisions around their processes and supply chains. Vishal believes moving away from the big data model can help smaller businesses embrace the positive impact of AI. “Companies of all sizes should be able to benefit from AI,” he says. “People do think it’s just for the big corporates, but that all stems from this idea that you need lots of data and it’s going to be expensive.”
Everyone talks about a future where we will need big data, but this is often driven by IT companies trying to sell server space"
ABOVE Prowler CEO Vishal Chatrath
Prowler has enjoyed a stellar 2019, securing additional investment and major new clients. And while Vishal believes more and more people are opening their eyes to the potential of AI, he is aware that the industry still has some work to do on its image. “I think one of the biggest problems is around expectations and the hype that comes with AI, because if you build up expectations and then don’t meet them, you get into difficulties," he says. “I think we’re now in a place where people are becoming more aware of the hype and having a healthy scepticism towards it. “When we go and talk to customers we just ask them about their problems and how we can solve them. We take the AI out of the customer’s world, because the method we use to solve their problem isn’t particularly relevant - whether we’re using a hammer, a spade, or an AI is a moot point.” prowler.io
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ISSUE 04
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